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High-resolution modeling framework for planning electricity systems with high penetration of renewables

Authors: André Pina; André Pina; Carlos A. Silva; Carlos A. Silva; Paulo Ferrão; Paulo Ferrão;

High-resolution modeling framework for planning electricity systems with high penetration of renewables

Abstract

The design of transition pathways for sustainable electricity systems with high penetrations of renewable energy sources requires the use of energy modeling tools that are able to account for two key aspects: the evolution of fossil fuels and technology prices, and the natural dynamics of renewable resources. However, the modeling methodologies most currently used focus on only one of these two aspects, which hinders their suitability for performing long-term analysis with high penetrations of renewable energy sources. This paper presents a modeling framework that is able to optimize the investment in new renewable generation capacity on the long-term while taking into account the hourly dynamics of electricity supply and demand. The framework combines two of the most used energy planning tools, each able to account for one of the aspects of the modeling of energy systems. The framework was applied to continental Portugal for the time period of 2005–2050, in order to identify optimal investment plans in new renewable and fossil generation capacity with the goal of achieving significant CO2 emissions reduction, under different scenarios. The results show that the inclusion of dynamics in the modeling methodology can help avoid overinvestment and reduce the excess of electricity from renewable energy sources that cannot be used by the system. These results can have a significant impact on the design of a sustainable electricity system and may lead to a diversification of the energy sources used.

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    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    144
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 1%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 1%
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Found an issue? Give us feedback
citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
144
Top 1%
Top 1%
Top 1%